Local ancestry and selection in admixed Sanjiang cattle

Abstract

The majority of native cattle are taurine ×  indicine cattle of diverse phenotypes in the central region of China. Sanjiang cattle, a typical breed in the central region, play a central role in human livelihood and have good adaptability, including resistance to dampness, heat, roughage, and disease, and are thus regarded as an important genetic resource. However, the genetic history of the successful breed remains unknown. Here, we sequenced 10 Sanjiang cattle genomes and compared them to the 70 genomes of 5 representative populations worldwide. We characterized the genomic diversity and breed formation process of Sanjiang cattle and found that Sanjiang cattle have a mixed ancestry of indicine (55.6%) and taurine (33.2%) dating to approximately 30 generations ago, which has shaped the genome of Sanjiang cattle. Through ancestral fragment inference, selective sweep and transcriptomic analysis, we identified several genes linked to lipid metabolism, immune regulation, and stress reactions across the mosaic genome of Sanjiang cattle showing an excess of taurine or indicine ancestry. Taurine ancestry might contribute to meat quality, and indicine ancestry is more conducive to adaptation to hot climate conditions, making Sanjiang cattle a valuable genetic resource for the central region of China. Our results will help us understand the evolutionary history and ancestry components of Sanjiang cattle, which will provide a reference for resource conservation and selective breeding of Chinese native cattle.

Keywords

Whole-genome sequencing / Local ancestry / Selection / Adaptation

References

[1] Abo-IsmailMK, LansinkN, AkannoE, KarisaBK, CrowleyJJ, MooreSS, BorkE, StothardP, BasarabJA, PlastowGS. Development and validation of a small SNP panel for feed efficiency in beef cattle. J Anim Sci, 2018, 96(2):375-397

[2] Adams HA, Southey BR, Everts RE, Marjani SL, Tian CX, Lewin HA, Rodriguez-Zas SL (2011) Transferase activity function and system development process are critical in cattle embryo development. Funct Integr Genomics 11(1):139–150. https://doi.org/10.1007/s10142-010-0189-9

[3] AishwaryaR, AbdullahCS, RemexNS, AlamS, MorshedM, NituS, HartmanB, KingJ, BhuiyanMAN, OrrAW. Molecular characterization of skeletal muscle dysfunction in sigma 1 receptor (Sigmar1) knockout mice. Am J Pathol, 2022, 192(1):160-177

[4] AlexanderDH, LangeK. Enhancements to the ADMIXTURE algorithm for individual ancestry estimation. BMC Bioinformatics, 2011, 12: 246

[5] ArgmannCA, CockTA, AuwerxJ. Peroxisome proliferator-activated receptor gamma: the more the merrier?. Eur J Clin Invest, 2005, 35(2):82-92

[6] AuwerxJ. PPARgamma, the ultimate thrifty gene. Diabetologia, 1999, 42(9):1033-1049

[7] BerringtonWR, IyerR, WellsRD, SmithKD, SkerrettSJ, HawnTR. NOD1 and NOD2 regulation of pulmonary innate immunity to Legionella pneumophila. Eur J Immunol, 2010, 40(12):3519-3527

[8] BhanuprakashV, SinghU, SengarGS, RajaT, SajjanarB, AlexR, KumarS, AlyethodiR, KumarA, SharmaA. Comparative expression profile of NOD1/2 and certain acute inflammatory cytokines in thermal-stressed cell culture model of native and crossbred cattle. Int J Biometeorol, 2017, 61(5):931-941

[9] BrowningSR, BrowningBL. Rapid and accurate haplotype phasing and missing-data inference for whole-genome association studies by use of localized haplotype clustering. Am J Hum Genet, 2007, 81(5):1084-1097

[10] Bu D, Luo H, Huo P, Wang Z, Zhang S, He Z, Wu Y, Zhao L, Liu J, Guo J, Fang S, Cao W, Yi L, Zhao Y, Kong L (2021) KOBAS-i: intelligent prioritization and exploratory visualization of biological functions for gene enrichment analysis. Nucleic Acids Res 49(W1):W317-W325. https://doi.org/10.1093/nar/gkab447

[11] BuggiottiL, YurchenkoAA, YudinNS, Vander JagtCJ, VorobievaNV, KusliyMA, VasilievSK, RodionovAN, BoronetskayaOI, ZinovievaNA, GraphodatskyAS, DaetwylerHD, LarkinDM. Demographic history, adaptation, and NRAP convergent evolution at amino acid residue 100 in the world Northernmost Cattle from Siberia. Mol Biol Evol, 2021, 38(8):3093-3110

[12] CancroMP, TomaykoMM. Memory B cells and plasma cells: the differentiative continuum of humoral immunity. Immunol Rev, 2021, 303(1):72-82

[13] ChenN, CaiY, ChenQ, LiR, WangK, HuangY, HuS, HuangS, ZhangH, ZhengZ, SongW, MaZ, MaY, DangR, ZhangZ, XuL, JiaY, LiuS, YueX, DengW, ZhangX, SunZ, LanX, HanJ, ChenH, BradleyDG, JiangY, LeiC. Whole-genome resequencing reveals world-wide ancestry and adaptive introgression events of domesticated cattle in East Asia. Nat Commun, 2018, 9(1):2337

[14] ChenQ, ZhanJ, ShenJ, QuK, HanifQ, LiuJ, ZhangJ, ChenN, ChenH, HuangB, LeiC. Whole-genome resequencing reveals diversity, global and local ancestry proportions in Yunling cattle. J Anim Breed Genet, 2020, 137(6):641-650

[15] DanecekP, AutonA, AbecasisG, AlbersCA, BanksE, DePristoMA, HandsakerRE, LunterG, MarthGT, SherryST, McVeanG, DurbinR. The variant call format and VCFtools. Bioinformatics, 2011, 27(15):2156-2158

[16] DavisRS. Fc receptor-like molecules. Annu Rev Immunol, 2007, 25(1):525-560

[17] DeckerJE, McKaySD, RolfMM, KimJ, Molina AlcaláA, SonstegardTS, HanotteO, GötherströmA, SeaburyCM, PraharaniL, BabarME, de AlmeidaCorreia, RegitanoL, YildizMA, HeatonMP, LiuWS, LeiCZ, ReecyJM, Saif-Ur-RehmanM, SchnabelRD, TaylorJF. Worldwide patterns of ancestry, divergence, and admixture in domesticated cattle. PLoS Genet, 2014, 10(3):e1004254

[18] DeGiorgioM, HuberCD, HubiszMJ, HellmannI, NielsenR. SweepFinder2: increased sensitivity, robustness and flexibility. Bioinformatics, 2016, 32(12):1895-1897

[19] Dias-AlvesT, MairalJ, BlumMG. Loter: a software package to infer local ancestry for a wide range of species. Mol Biol Evol, 2018, 35(9):2318-2326

[20] FanYY, ZanLS, FuCZ, TianWQ, WangHB, LiuYY, XinYP. Three novel SNPs in the coding region of PPARγ gene and their associations with meat quality traits in cattle. Mol Biol Rep, 2011, 38(1):131-137

[21] Fernandes JúniorGA, de OliveiraHN, CarvalheiroR, CardosoDF, FonsecaLFS, VenturaRV, de AlbuquerqueLG. Whole-genome sequencing provides new insights into genetic mechanisms of tropical adaptation in Nellore (Bos primigenius indicus). Sci Rep, 2020, 10(1):1-7

[22] GoszczynskiDE, MazzuccoJP, RipoliMV, VillarrealEL, Rogberg-MuñozA, MezzadraCA, MelucciLM, GiovambattistaG. Genetic characterisation of PPARG, CEBPA and RXRA, and their influence on meat quality traits in cattle. J Anim Sci Technol, 2016, 58: 14

[23] GraaeA-S, GrarupN, Ribel-MadsenR, LystbækSH, BoesgaardT, StaigerH, FritscheA, WellnerN, SulekK, KjolbyM. ADAMTS9 regulates skeletal muscle insulin sensitivity through extracellular matrix alterations. Diabetes, 2019, 68(3):502-514

[24] GuilletC, Huchet-CadiouC, GascanH, LÉOTY, C.. Changes in CNTF receptor α expression in rat skeletal muscle during the recovery period after hindlimb suspension. Acta Physiol Scand, 1998, 163(3):273

[25] GuoY, FengW, SySM, HuenMS. ATM-dependent phosphorylation of the fanconi anemia protein PALB2 promotes the DNA damage response. J Biol Chem, 2015, 290(46):27545-27556

[26] HabermannA, SchroerTA, GriffithsG, BurkhardtJK. Immunolocalization of cytoplasmic dynein and dynactin subunits in cultured macrophages: enrichment on early endocytic organelles. J Cell Sci, 2001, 114(Pt 1):229-240

[27] HaoZ, LvD, GeY, ShiJ, WeijersD, YuG, ChenJ. RIdeogram: drawing SVG graphics to visualize and map genome-wide data on the idiograms. PeerJ Comput Sci, 2020, 6: e251

[28] HouT, ZhangR, JianC, DingW, WangX. NDUFAB1 protects heart by coordinating mitochondrial respiratory complex and supercomplex assembly. Cold Spring Harbor Laboratory, 2018

[29] JungersKA, Le GoffC, SomervilleRP, ApteSS. Adamts9 is widely expressed during mouse embryo development. Gene Expr Patterns, 2005, 5(5):609-617

[30] KamiK, MorikawaY, SekimotoM, SenbaE. Gene expression of receptors for IL-6, LIF, and CNTF in regenerating skeletal muscles. Journal of Histochemistry & Cytochemistry Official Journal of the Histochemistry Society, 2000, 48(9):1203-1213

[31] Keestra-GounderAM, ByndlossMX, SeyffertN, YoungBM, Chávez-ArroyoA, TsaiAY, CevallosSA, WinterMG, PhamOH, TiffanyCR. NOD1 and NOD2 signalling links ER stress with inflammation. Nature, 2016, 532(7599):394-397

[32] KimD, LangmeadB, SalzbergSL. HISAT: a fast spliced aligner with low memory requirements. Nat Methods, 2015, 12(4):357-360

[33] KimCC, BaccarellaAM, BayatA, PepperM, FontanaMF. FCRL5+ memory B cells exhibit robust recall responses. Cell Rep, 2019, 27(5):1446-1460

[34] KumarS, StecherG, LiM, KnyazC, TamuraK. MEGA X: Molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol, 2018, 35(6):1547-1549

[35] LeeKT, ChungWH, LeeSY, ChoiJW, KimJ, LimD, LeeS, JangGW, KimB, ChoyYH, LiaoX, StothardP, MooreSS, LeeSH, AhnS, KimN, KimTH. Whole-genome resequencing of Hanwoo (Korean cattle) and insight into regions of homozygosity. BMC Genomics, 2013, 14: 519

[36] LetunicI, BorkP. Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Res, 2019, 47(W1):W256-w259

[37] LiH, DurbinR. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics, 2009, 25(14):1754-1760

[38] Lizarraga-Mollinedo E, Carreras-Badosa G, Xargay-Torrent S, Remesar X, Mas-Pares B, Prats-Puig A, de Zegher F, Ibáñez L, López-Bermejo A, Bassols J (2022) Catch-up growth in juvenile rats, fat expansion, and dysregulation of visceral adipose tissue. Pediatr Res 91(1):107–115. https://doi.org/10.1038/s41390-021-01422-9

[39] LohP-R, LipsonM, PattersonN, MoorjaniP, PickrellJK, ReichD, BergerB. Inferring admixture histories of human populations using linkage disequilibrium. Genetics, 2013, 193(4):1233-1254

[40] LoveMI, HuberW, AndersS. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol, 2014, 15(12):1-21

[41] MacHughDE, ShriverMD, LoftusRT, CunninghamP, BradleyDG. Microsatellite DNA variation and the evolution, domestication and phylogeography of taurine and zebu cattle (Bos taurus and Bos indicus). Genetics, 1997, 146(3):1071-1086

[42] Maloyan A, Horowitz M (2022) beta-Adrenergic signaling and thyroid hormones affect HSP72 expression during heat acclimation. J Appl Physiol 93(1):107–115. https://doi.org/10.1152/japplphysiol.01122.2001

[43] ManichaikulA, MychaleckyjJC, RichSS, DalyK, SaleM, ChenWM. Robust relationship inference in genome-wide association studies. Bioinformatics, 2010, 26(22):2867-2873

[44] MatesanzN, BernardoE, Acín-PérezR, ManieriE, Pérez-SieiraS, Hernández-CosidoL, Montalvo-RomeralV, MoraA, RodríguezE, Leiva-VegaL, Lechuga-ViecoAV, Ruiz-CabelloJ, TorresJL, Crespo-RuizM, CentenoF, ÁlvarezCV, MarcosM, EnríquezJA, NogueirasR, SabioG. MKK6 controls T3-mediated browning of white adipose tissue. Nat Commun, 2017, 8(1):856

[45] MelloukN, RameC, NaquinD, JaszczyszynY, TouzéJL. Impact of the severity of negative energy balance on gene expression in the subcutaneous adipose tissue of periparturient primiparous Holstein dairy cows: identification of potential novel metabolic signals for the reproductive system. PloS one, 2019, 14(9):e0222954

[46] NekrutenkoA, TaylorJ. Next-generation sequencing data interpretation: enhancing reproducibility and accessibility. Nat Rev Genet, 2012, 13(9):667-672

[47] NielsenR, WilliamsonS, KimY, HubiszMJ, ClarkAG, BustamanteC. Genomic scans for selective sweeps using SNP data. Genome Res, 2005, 15(11):1566-1575

[48] PerteaM, PerteaGM, AntonescuCM, ChangT-C, MendellJT, SalzbergSL. StringTie enables improved reconstruction of a transcriptome from RNA-seq reads. Nat Biotechnol, 2015, 33(3):290-295

[49] PurcellS, NealeB, Todd-BrownK, ThomasL, FerreiraMA, BenderD, MallerJ, SklarP, de BakkerPI, DalyMJ, ShamPC. PLINK: a tool set for whole-genome association and population-based linkage analyses. Am J Hum Genet, 2007, 81(3):559-575

[50] Reid GA (1991). Molecular cloning: A laboratory manual, 2nd edn: Cold Spring Harbor Laboratory Press, New York

[51] SalavatiM, BushSJ, Palma-VeraS, McCullochMEB, HumeDA, ClarkEL. Elimination of reference mapping bias reveals robust immune related allele-specific expression in crossbred sheep. Front Genet, 2019, 10: 863

[52] SerãoNV, González-PeñaD, BeeverJE, FaulknerDB, SoutheyBR, Rodriguez-ZasSL. Single nucleotide polymorphisms and haplotypes associated with feed efficiency in beef cattle. BMC Genet, 2013, 14: 94

[53] SevaneN, ArmstrongE, CortésO, WienerP, WongRP, DunnerS. Association of bovine meat quality traits with genes included in the PPARG and PPARGC1A networks. Meat Sci, 2013, 94(3):328-335

[54] ShenJ, YuJ, DaiX, LiM, WangG, ChenN, ChenH, LeiC, DangR. Genomic analyses reveal distinct genetic architectures and selective pressures in Chinese donkeys. J Genet Genomics, 2021, 48(8):737-745

[55] Smith-Anttila CJA, Bensing S, Alimohammadi M, Dalin F, Oscarson M, Zhang MD, Perheentupa J, Husebye ES, Gustafsson J, Björklund P, Fransson A, Nordmark G, Rönnblom L, Meloni A, Scott RJ, Hökfelt T, Crock PA, Kämpe O. (2017) Identification of endothelin-converting enzyme-2 as an autoantigen in autoimmune polyendocrine syndrome type 1. Autoimmunity 50(4):223–231. https://doi.org/10.1080/08916934.2017.1332183

[56] SzpiechZA, HernandezRD. selscan: an efficient multithreaded program to perform EHH-based scans for positive selection. Mol Biol Evol, 2014, 31(10):2824-2827

[57] TangQ, ZhangX, WangX, WangK, YanH, ZhuH, LanX, LeiQ, PanC. Detection of two insertion/deletions (indels) within the ADAMTS9 gene and their associations with growth traits in goat. Small Rumin Res, 2019, 180: 9-14

[58] TsudaK, Kawahara-MikiR, SanoS, ImaiM, NoguchiT, InayoshiY, KonoT. Abundant sequence divergence in the native Japanese cattle Mishima-Ushi (Bos taurus) detected using whole-genome sequencing. Genomics, 2013, 102(4):372-378

[59] UtsunomiyaYT, MilanesiM, FortesMRS, Porto-NetoLR, UtsunomiyaATH, SilvaM, GarciaJF, Ajmone-MarsanP. Genomic clues of the evolutionary history of Bos indicus cattle. Anim Genet, 2019, 50(6):557-568

[60] WangK, LiM, HakonarsonH. ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data. Nucleic Acids Res, 2010, 38(16):e164-e164

[61] WangkumhangP, GreenfieldM, HellenthalG. An efficient method to identify, date, and describe admixture events using haplotype information. Genome Res, 2022, 32(8):1553-1564

[62] Weis J, Lie DC, Ragoss U, Züchner SL, Schröder JM, Karpati G, Farruggella T, Stahl N, Yancopoulos GD, DiStefano PS (1998) Increased expression of CNTF receptor alpha in denervated human skeletal muscle. J Neuropathol Exp Neurol 57(9):850–857. https://doi.org/10.1097/00005072-199809000-00006

[63] XiaB, ShengQ, NakanishiK, OhashiA, WuJ, ChristN, LiuX, JasinM, CouchFJ, LivingstonDM. Control of BRCA2 cellular and clinical functions by a nuclear partner, PALB2. Mol Cell, 2006, 22(6):719-729

[64] XiaX, ZhangS, ZhangH, ZhangZ, ChenN, LiZ, SunH, LiuX, LyuS, WangX, LiZ, YangP, XuJ, DingX, ShiQ, WangE, RuB, XuZ, LeiC, ChenH, HuangY. Assessing genomic diversity and signatures of selection in Jiaxian Red cattle using whole-genome sequencing data. BMC Genomics, 2021, 22(1):43

[65] Xia X, Qu K, Wang Y, Sinding M-H S, Wang F, Hanif Q, Ahmed Z, Lenstra J A, Han J, Lei C, Chen N (2023) Global dispersal and adaptive evolution of domestic cattle: a genomic perspective. Stress Biology 3(1):1–8. https://doi.org/10.1007/s44154-023-00085-2

[66] YanagisawaH, HammerRE, RichardsonJA, EmotoN, YanagisawaM. Disruption of ECE-1 and ECE-2 reveals a role for endothelin-converting enzyme-2 in murine cardiac development. J Clin Investig, 2000, 105(10):1373-1382

[67] YangH, ShenH, LiJ, StanfordKI, GuoL-W. Sigma-1 receptor ablation impedes adipocyte-like differentiation of mouse embryonic fibroblasts. Cellular signalling, 2020, 75: 109732

[68] ZhangW, GaoX, ZhangY, ZhaoY, ZhangJ, JiaY, ZhuB, XuL, ZhangL, GaoH, LiJ, ChenY. Genome-wide assessment of genetic diversity and population structure insights into admixture and introgression in Chinese indigenous cattle. BMC Genet, 2018, 19(1):114

[69] ZhangC, DongSS, XuJY, HeWM, YangTL. PopLDdecay: a fast and effective tool for linkage disequilibrium decay analysis based on variant call format files. Bioinformatics, 2019, 35(10):1786-1788

[70] ZhangK, LenstraJA, ZhangS, LiuW, LiuJ. Evolution and domestication of the Bovini species. Anim Genet, 2020, 51(5):637-657

[71] Zhou Z, Ikegaya Y, Koyama R (2019) The Astrocytic cAMP Pathway in Health and Disease. Int J Mol Sci 20(3):779. https://doi.org/10.3390/ijms20030779

Funding

China Agriculture Research System-the National Beef Cattle and Yak Industrial Technology System(CARS-37); National Natural Science Foundation of China(31872317); China Postdoctoral Science Foundation(2020M683587)); Shaanxi Key Laboratory of Flight Control and Simulation Technology(2022KJXX-77); Natural Science Basic Research Program of Shaanxi(2021JQ-137); Fundamental Research Funds for the Central Universities; Scientific Research Fund of the Department of Education of Yunnan(2022J0830)